交通运输系统工程与信息 ›› 2021, Vol. 21 ›› Issue (5): 190-197.

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新冠肺炎交通防控政策对长沙市人口流动的影响

闫常鑫1,王彬1,陈理2,向往* 2,王云3,闫学东3   

  1. 1. 长沙市规划勘测设计研究院,长沙 410007;2. 长沙理工大学,交通运输工程学院,长沙 410114; 3. 北京交通大学,交通运输学院,北京 100044
  • 收稿日期:2021-04-20 修回日期:2021-05-19 接受日期:2021-06-17 出版日期:2021-10-25 发布日期:2021-10-21
  • 作者简介:闫常鑫(1971- ),男,湖南长沙人,高级工程师,注册规划师。
  • 基金资助:
    国家自然科学基金;湖南省自然科学基金

Impacts of COVID-19 Traffic Control Policy on Population Flows in Changsha

YAN Chang-xin1 , WANG Bin1 , CHEN Li2 , XIANG Wang* 2 , WANG Yun3 , YAN Xue-dong3   

  1. 1. Changsha Planning & Design Survey Research Institute, Changsha 410007, China; 2. School of Traffic & Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China; 3. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
  • Received:2021-04-20 Revised:2021-05-19 Accepted:2021-06-17 Online:2021-10-25 Published:2021-10-21
  • Supported by:
    National Natural Science Foundation of China;Natural Science Foundation of Hunan Province, China

摘要: 为探究新冠肺炎疫情下交通防控政策对长沙市人口流动的影响,本文根据长沙市在新冠 肺炎疫情期间颁布的交通防控政策和疫情实时防控情况划分防控阶段,基于百度迁徙大数据,利 用双重差分模型,识别长沙市不同阶段的交通防控政策以及量化防控效果,分析交通防控政策对 长沙市人口流动的影响。结果显示,长沙市在交通管制阶段,平均人口迁出强度、平均人口迁入 强度及城市内部出行强度分别下降了83.68%、69.24%及59.74%,有效地控制了人口流动,降低了 疫情扩散危险。在交通恢复阶段,长沙市人口流动强度逐渐反弹,城市内部出行强度基本恢复到 2019年同期水平。本文研究结果显示了交通管制对疫情扩散限制的有效性,为常态化疫情防控 下精准防控政策和复工复产政策制定提供参考。

关键词: 城市交通, 交通防控政策, 双重差分模型, 人口流动, 百度迁徙大数据

Abstract: To investigate the impact of COVID-19 traffic control policies on population flow in Changsha, this paper divided the prevention and traffic control policies into different stages corresponding to the real-time epidemic situation in Changsha. Based on Baidu migration big data, the difference- in- difference model was used to identify different stages of traffic prevention and control policies and quantify the effect of prevention. With the traffic control policy implemented during COVID- 19, the average inflow intensity of Changsha City decreased by 83.68% , the average outflow intensity decreased by 69.24% and the internal travel intensity respectively, decreased by 59.74%. After the end of the traffic control policies, the population flow intensity of Changsha City gradually rebounded, and the urban internal travel intensity basically recovered to the same level as in 2019. The results indicated the effectiveness of the traffic control policies on the limitation of population flow and epidemic spread. The results also provide reference for making effective prevention and control policies for the normalized COVID-19 epidemic situations.

Key words: urban traffic, traffic control policy, difference-in- difference model, population flow, baidu migration big data

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